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Design of an ITS for Industrial Enterprises

  • Alexandr RakhmangulovEmail author
  • Aleksander Sładkowski
  • Nikita Osintsev
Chapter
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 32)

Abstract

One of the factors limiting the increase in quality of traffic with the increasing complexity of the freight traffic in Russia is the lack of interaction consistency of the main modes of transport and transport uncommon in areas of direct transport service production and transport units. Lack of practical operating experience of intelligent transport systems in Russian enterprises, poor prevalence of well-known methods of accumulation and analysis of knowledge in transport, decision-making (genetic algorithms, neural networks, knowledge bases, Big Data methods, etc.) require improvement of the existing interaction methodology between industry and transport, in particular transport and technological systems providing direct cargo transport services. This methodology should be based not only on modern progress in technology and organization of rail transport, but also taken into account the economic and informational factors and constraints that arise in the interaction of industrial and mainline rail. This article proposes an approach to the formation and composition of intelligent transport systems in industry. This approach is based on the original combination of analytical and simulation models of transport and technological system realizing the complex of transport and logistic methods of functioning organization of rail transport and technological systems. Intelligent transport system of proposed functional composition is focused on improving the efficiency of interaction between production and transport in terms of complicating the structure of freight traffic and the increasing quality requirements for freight.

Keywords

Resource Network Processing Capacity Industrial Enterprise Railway Station Freight Transport 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Alexandr Rakhmangulov
    • 1
    Email author
  • Aleksander Sładkowski
    • 2
  • Nikita Osintsev
    • 1
  1. 1.Magnitogorsk State Technical UniversityMagnitogorskRussia
  2. 2.Silesian University of TechnologyGliwicePoland

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